Physiological monitoring devices and methods using optical sensors

ABSTRACT

A monitoring device configured to be attached to a subject includes a photoplethysmography (PPG) sensor configured to measure a plurality of physiological parameters from the subject, a motion sensor configured to detect an activity state of the subject, and a processor coupled to the PPG sensor and the motion sensor. The PPG sensor is configured to measure each physiological parameter in a respective one of a plurality of time intervals. The processor instructs the PPG sensor to measure a first one of the plurality of physiological parameters if the activity state is at or above a threshold, and to measure a second one of the plurality of physiological parameters if the activity state is below the threshold.

RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 16/503,191, filed Jul. 3, 2019, which is acontinuation application of pending U.S. patent application Ser. No.14/807,149, filed Jul. 23, 2015, and which claims the benefit of andpriority to U.S. Provisional Patent Application No. 62/030,951 filedJul. 30, 2014, and U.S. Provisional Patent Application No. 62/109,196filed Jan. 29, 2015, the disclosures of which are incorporated herein byreference as if set forth in their entireties.

FIELD OF THE INVENTION

The present invention relates generally to monitoring devices and, moreparticularly, to monitoring devices for measuring physiologicalinformation.

BACKGROUND OF THE INVENTION

Photoplethysmography (PPG) is based upon shining light into the humanbody and measuring how the scattered light intensity changes with eachpulse of blood flow. The scattered light intensity will change in timewith respect to changes in blood flow or blood opacity associated withheart beats, breaths, blood oxygen level (SpO₂), and the like. Such asensing methodology may require the magnitude of light energy reachingthe volume of flesh being interrogted to be steady and consistent sothat small changes in the quantity of scattered photons can beattributed to varying blood flow. If the incidental and scattered photoncount magnitude changes due to light coupling variation between thesource or detector and the skin or other body tissue, then the signal ofinterest can be difficult to ascertain due to large photon countvariability caused by motion artifacts. Changes in the surface area (andvolume) of skin or other body tissue being impacted with photons, orvarying skin surface curvature reflecting significant portions of thephotons may also significantly impact optical coupling efficiency.Physical activity, such a walking, cycling, running, etc., may causemotion artifacts in the optical scatter signal from the body, andtime-varying changes in photon intensity due to motion artifacts mayswamp-out time-varying changes in photon intensity due to blood flowchanges. Each of these changes in optical coupling can dramaticallyreduce the signal-to-noise ratio (S/N) of biometric PPG information tototal time-varying photonic interrogation count. This can result in amuch lower accuracy in metrics derived from PPG data, such as heart rateand breathing rate.

An earphone, such as a headset, earbud, etc., may be a good choice forincorporation of a photoplethysmograph device because it is a formfactor that individuals are familiar with, it is a device that iscommonly worn for long periods of time, and it frequently is used duringexercise which is a time when individuals may benefit most from havingaccurate heart rate data (or other physiological data). Unfortunately,incorporation of a photoplethysmograph device into an earphone posesseveral challenges. For example, earphones may be uncomfortable to wearfor long periods of time, particularly if they deform the ear surface.Moreover, human ear anatomy may vary significantly from person toperson, so finding an earbud form that will fit comfortably in many earsmay pose significant challenges. In addition, earbuds made for vigorousphysical activity typically incorporate an elastomeric surface and/orelastomeric features to function as springs that dampen earbudacceleration within the ear. Although, these features may facilitateretention of an earbud within an ear during high acceleration and impactmodalities, they may not adequately address optical skin couplingrequirements needed to achieve quality photoplethysmography.

Conventional photoplethysmography devices, as illustrated for example inFIGS. 1A-1C, typically suffer from reduced skin coupling as a result ofsubject motion. For example, most conventional photoplethysmographydevices use a spring to clip the sensor onto either an earlobe (FIG. 1A)or a fingertip (FIG. 1B). Unfortunately, these conventional devices tendto have a large mass and may not maintain consistent skin contact whensubjected to large accelerations, such as when a subject is exercising.

A conventional earbud device that performs photoplethysmography in theear is the MX-D100 player from Perception Digital of Wanchai, Hong Kong(www.perceptiondigital.com). This earbud device, illustrated in FIG. 1Cand indicated as 10, incorporates a spring biased member 12 to improvePPG signal quality. The member 12 is urged by a spring or other biasingelement (not shown) in the direction of arrow A₁, as indicated in FIG.1C. The spring biased member 12 forcibly presses the entire earbud 10within the ear E of a subject to minimize motion of the entire earbud10. However, there are several drawbacks to the device 10 of FIG. 1C.For example, the source/sensor module is coupled to the entire earbudmass and, as such, may experience larger translation distances resultingin greater signal variability when the ear undergoes accelerations. Inaddition, because the earbud 10 is held in place with one primary springforce direction, significant discomfort can be experienced by the enduser. Moreover, the earbud motion is only constrained in one direction(i.e., the direction indicated by A₁) due to the single spring forcedirection.

Because PPG used in wearable devices employs an optical technology,requiring the powering of optical emitters and microprocessors via awearable battery, managing power consumption can be challenging. Forexample, high-power algorithms may be required to accurately measureheart rate during exercise. Thus, employing a high-power algorithmduring exercise may have the benefit of accurately monitoring heart rateduring exercise but may also have the unwanted effect of draining thebattery of the wearable device such that the device will not have enoughpower to measure a subject over the course of a day or week duringnon-exercising periods.

SUMMARY

It should be appreciated that this Summary is provided to introduce aselection of concepts in a simplified form, the concepts being furtherdescribed below in the Detailed Description. This Summary is notintended to identify key features or essential features of thisdisclosure, nor is it intended to limit the scope of the invention.

According to some embodiments of the present invention, a monitoringdevice configured to be attached to a body of a subject includes asensor that is configured to detect and/or measure physiologicalinformation from the subject and a processor coupled to the sensor thatis configured to receive and analyze signals produced by the sensor. Thesensor may be an optical sensor that includes at least one opticalemitter and at least one optical detector, although various other typesof sensors may be utilized. The processor is configured to change thesignal analysis frequency (i.e., the signal sampling rate), sensoralgorithm, and/or sensor interrogation power in response to detecting achange in subject activity. For example, in some embodiments, theprocessor increases signal analysis frequency and/or sensorinterrogation power in response to detecting an increase in subjectactivity, and decreases signal analysis frequency and/or sensorinterrogation power in response to detecting a decrease in subjectactivity. In other embodiments, the processor may change the sensoralgorithm in response to a change in subject activity. For example, theprocessor may implement frequency-domain digital signal processing inresponse to detecting high subject activity, and implement time-domaindigital signal processing in response to detecting low subject activity.The frequency- and time-domain algorithms represent two different signalextraction methods for extracting accurate biometrics from opticalsensor signals, where the frequency-domain algorithm may requiresubstantially greater processing power than that of the time-domainalgorithm.

In some embodiments, detecting a change in subject activity comprisesdetecting a change in at least one subject vital sign, such as subjectheart rate, subject blood pressure, subject temperature, subjectrespiration rate, subject perspiration rate, etc. In other embodiments,the sensor includes a motion sensor, such as an accelerometer,gyroscope, etc., and detecting a change in subject activity includesdetecting a change in subject motion via the motion sensor. In someembodiments, detecting a change in subject activity may includepredicting a type of activity the subject is engaged in.

According to some embodiments of the present invention, a method ofmonitoring a subject via a monitoring device having a sensor includeschanging signal analysis frequency and/or sensor interrogation power inresponse to detecting a change in subject activity. In some embodiments,detecting a change in subject activity comprises detecting a change inat least one subject vital sign, such as subject heart rate, subjectblood pressure, subject temperature, subject respiration rate, and/orsubject perspiration rate, etc. In other embodiments, detecting a changein subject activity comprises detecting a change in subject motion via amotion sensor associated with the sensor.

In some embodiments, changing signal analysis frequency and/or sensorinterrogation power in response to detecting a change in subjectactivity includes increasing signal analysis frequency and/or sensorinterrogation power in response to detecting an increase in subjectactivity, and decreasing signal analysis frequency and/or sensorinterrogation power in response to detecting a decrease in subjectactivity. In other embodiments, the processor is configured to implementfrequency-domain digital signal processing in response to detecting highsubject activity, and to implement time-domain digital signal processingin response to detecting low subject activity.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject includes a sensorconfigured to detect and/or measure physiological information from thesubject. The monitoring device also includes a processor coupled to thesensor that is configured to receive and analyze signals produced by thesensor. The sensor may be an optical sensor that includes at least oneoptical emitter and at least one optical detector, although variousother types of sensors may be utilized. The processor is configured tochange signal analysis frequency and/or sensor interrogation power inresponse to detecting, via the sensor or another sensor, a change in theat least one environmental condition, such as temperature, humidity, airquality, barometric pressure, radiation, light intensity, and sound. Forexample, in some embodiments, the processor increases signal analysisfrequency and/or sensor interrogation power in response to detecting anincrease in the at least one environmental condition, and decreasessignal analysis frequency and/or sensor interrogation power in responseto detecting a decrease in the at least one environmental condition.

In some embodiments, a method of monitoring a subject via a monitoringdevice includes changing signal analysis frequency and/or sensorinterrogation power in response to detecting a change in at least oneenvironmental condition. For example, in some embodiments, changingsignal analysis frequency and/or sensor interrogation power in responseto detecting a change in at least one environmental condition includesincreasing signal analysis frequency and/or sensor interrogation powerin response to detecting an increase in at least one environmentalcondition, and decreasing signal analysis frequency and/or sensorinterrogation power in response to detecting a decrease in at least oneenvironmental condition.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject includes a clock (e.g., adigital clock, an internal software clock, etc.) or is in communicationwith a clock, a sensor configured to detect and/or measure physiologicalinformation from the subject, and a processor coupled to the clock andthe sensor. The sensor may be an optical sensor that includes at leastone optical emitter and at least one optical detector, although variousother types of sensors may be utilized. The processor is configured toreceive and analyze signals produced by the sensor, and is configured tochange signal analysis frequency and/or sensor interrogation power atone or more predetermined times. For example, in some embodiments, theprocessor increases signal analysis frequency and/or sensorinterrogation power at a first time, and decreases signal analysisfrequency and/or sensor interrogation power at a second time. In otherembodiments, the processor adjusts signal analysis frequency and/orsensor interrogation power according to a circadian rhythm of thesubject.

According to some embodiments, a method of monitoring a subject via amonitoring device includes changing signal analysis frequency and/orsensor interrogation power at one or more predetermined times. In someembodiments, changing signal analysis frequency and/or sensorinterrogation power at one or more predetermined times includesincreasing signal analysis frequency and/or sensor interrogation powerat a first time, and decreasing signal analysis frequency and/or sensorinterrogation power at a second time. In other embodiments, changingsignal analysis frequency and/or sensor interrogation power at one ormore predetermined times comprises adjusting signal analysis frequencyand/or sensor interrogation power according to a circadian rhythm of thesubject.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject includes a location sensoror is in communication with a location sensor, a sensor configured todetect and/or measure physiological information from the subject, and aprocessor coupled to the location sensor and the sensor. The sensor maybe an optical sensor that includes at least one optical emitter and atleast one optical detector, although various other types of sensors maybe utilized. The processor is configured to receive and analyze signalsproduced by the sensor and to change signal analysis frequency and/orsensor interrogation power when the subject has changed locations. Forexample, in some embodiments, the processor increases signal analysisfrequency and/or sensor interrogation power when the subject is at aparticular location, and decreases signal analysis frequency and/orsensor interrogation power when the subject is no longer at theparticular location

According to some embodiments, a method of monitoring a subject via amonitoring device includes changing signal analysis frequency and/orsensor interrogation power when a location sensor associated with themonitoring device indicates the subject has changed locations. Forexample, in some embodiments, signal analysis frequency and/or sensorinterrogation power is increased when the subject is at a particularlocation, and signal analysis frequency and/or sensor interrogationpower is decreased when the subject is no longer at the particularlocation.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject includes a sensorconfigured to detect and/or measure physiological information from thesubject, and a processor coupled to the sensor. The sensor includes atleast one optical emitter and at least one optical detector. Theprocessor is configured to receive and analyze signals produced by thesensor, and is configured to change the wavelength of light emitted bythe at least one optical emitter in response to detecting a change insubject activity. In some embodiments, the processor instructs the atleast one optical emitter to emit shorter wavelength light (e.g., adecrease in wavelength by 100 nm or more) in response to detecting anincrease in subject activity, and instructs the at least one opticalemitter to emit longer wavelength light (e.g., an increase in wavelengthby 100 nm or more) in response to detecting an decrease in subjectactivity.

In some embodiments, detecting a change in subject activity comprisesdetecting a change in at least one subject vital sign, such as subjectheart rate, subject blood pressure, subject temperature, subjectrespiration rate, subject perspiration rate, etc. In other embodiments,the sensor includes a motion sensor, such as an accelerometer,gyroscope, etc., and detecting a change in subject activity includesdetecting a change in subject motion via the motion sensor.

In some embodiments, detecting a change in subject activity may includepredicting a type of activity the subject is engaged in.

According to some embodiments of the present invention, a method ofmonitoring a subject via a monitoring device having a sensor includeschanging wavelength of light emitted by at least one optical emitterassociated with the sensor in response to detecting a change in subjectactivity. For example, in some embodiments, changing wavelength of lightemitted by the at least one optical emitter may include instructing theat least one optical emitter to emit shorter wavelength light inresponse to detecting an increase in subject activity, and instructingthe at least one optical emitter to emit longer wavelength light inresponse to detecting an decrease in subject activity.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject includes a sensorconfigured to detect and/or measure physiological information from thesubject, and a processor coupled to the sensor and configured to receiveand analyze signals produced by the sensor. The sensor comprises atleast one optical emitter and at least one optical detector, and theprocessor instructs the at least one optical emitter to emit a differentwavelength of light during each of a series of respective time intervalssuch that a respective different physiological parameter can be measuredfrom the subject during each time interval via the at least one opticaldetector.

According to some embodiments of the present invention, a method ofmonitoring a subject via a monitoring device having a sensor with atleast one optical emitter and at least one optical detector comprisesemitting a different wavelength of light during each of a series ofrespective time intervals, and measuring a respective differentphysiological parameter of the subject during each time interval via theat least one optical detector.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject includes a sensorconfigured to detect and/or measure physiological information from thesubject, and a processor coupled to the sensor. The processor isconfigured to receive and analyze signals produced by the sensor, and isconfigured to change signal analysis frequency and/or change sensorinterrogation power in response to detecting a change in subject stresslevel (e.g., by detecting a change in at least one subject vital sign,such as heart rate, blood pressure, temperature, respiration rate,and/or perspiration rate). For example, in some embodiments, theprocessor increases signal analysis frequency and/or increases sensorinterrogation power in response to detecting an increase in subjectstress level, and decreases signal analysis frequency and/or decreasessensor interrogation power in response to detecting a decrease insubject stress level.

In some embodiments, the sensor comprises a voice recognition system.The processor is configured to increase processing power for the voicerecognition system in response to detecting an increase in subjectstress level, and to decrease processing power for the voice recognitionsystem in response to detecting an decrease in subject stress level.

In some embodiments, the sensor is in communication with a userinterface. In some embodiments, the processor may be configured toincrease user interface brightness and/or font size of alphanumericcharacters displayed on the user interface in response to detecting anincrease in subject stress level, and is configured to decrease userinterface brightness and/or font size of alphanumeric charactersdisplayed on the user interface in response to detecting a decrease insubject stress level. In some embodiments, the processor may beconfigured to enlarge an image displayed within the user interfaceand/or make an image displayed within the user interface easier toview/comprehend (e.g., increase the resolution of the image, etc.) inresponse to detecting an increase in subject stress level. The processormay be configured to decrease an image displayed within the userinterface and/or reduce the resolution of an image displayed within theuser interface in response to detecting an increase in subject stresslevel.

According to some embodiments of the present invention, a method ofmonitoring a subject via a monitoring device having a sensor includeschanging signal analysis frequency and/or changing sensor interrogationpower via the processor in response to detecting a change in subjectstress level. For example, in some embodiments signal analysis frequencyand/or sensor interrogation power is increased in response to detectingan increase in subject stress level, and signal analysis frequencyand/or sensor interrogation power is decreased in response to detectinga decrease in subject stress level.

In some embodiments, the sensor comprises a voice recognition system,and the method includes increasing processing power for the voicerecognition system in response to detecting an increase in subjectstress level, and decreasing processing power for the voice recognitionsystem in response to detecting a decrease in subject stress level.

In some embodiments, the sensor is in communication with a userinterface, and the method includes increasing user interface brightnessand/or font size of alphanumeric characters displayed on the userinterface in response to detecting an increase in subject stress level,and decreasing user interface brightness and/or font size ofalphanumeric characters displayed on the user interface in response todetecting a decrease in subject stress level.

According to other embodiments of the present invention, a method ofmonitoring a subject wearing a PPG sensor device having at least oneprocessor includes processing PPG sensor readings via the at least oneprocessor to determine if the subject is located indoors or outdoors,and selecting a PPG sensor polling routine associated with indoor oroutdoor conditions depending on whether the subject is located indoorsor outdoors, respectively. In some embodiments, if the subject islocated indoors, the PPG sensor polling routine is configured to directthe PPG sensor to utilize light with at least one visible wavelength andat least one infrared (IR) wavelength, and if the subject is locatedoutdoors, the PPG sensor polling routine is configured to direct the PPGsensor to utilize light with at least two distinct IR wavelengths or twodifferent IR wavelength bands. The method may further includedetermining blood and/or tissue oxygenation of the subject via the PPGsensor.

Monitoring devices in accordance with some embodiments of the presentinvention may be configured to be positioned at or within an ear of asubject or secured to an appendage or other body location of the subject

Monitoring devices, according to embodiments of the present invention,are advantageous over conventional monitoring devices because, bychanging signal analysis frequency and/or sensor interrogation power,power savings may be incurred. Moreover, increasing sensing power orsampling frequency may allow for finer, more accurate sensor data to becollected during periods of rapid body activity, e.g., duringexercising, running, walking, etc. Conversely sensor data changes duringperiods of inactivity may be infrequent and require significantly lowerpower to achieve sufficient data resolution to accurately describephysiological changes.

It is noted that aspects of the invention described with respect to oneembodiment may be incorporated in a different embodiment although notspecifically described relative thereto. That is, all embodiments and/orfeatures of any embodiment can be combined in any way and/orcombination. Applicant reserves the right to change any originally filedclaim or file any new claim accordingly, including the right to be ableto amend any originally filed claim to depend from and/or incorporateany feature of any other claim although not originally claimed in thatmanner. These and other objects and/or aspects of the present inventionare explained in detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which form a part of the specification,illustrate various embodiments of the present invention. The drawingsand description together serve to fully explain embodiments of thepresent invention.

FIG. 1A is a perspective view of a conventional PPG device attached tothe ear of a person.

FIG. 1B is a perspective view of a conventional PPG device attached to afinger of a person.

FIG. 1C illustrates a conventional PPG device attached to the ear of aperson, and wherein a biasing element is utilized to retain thephotoplethysmography device in the person's ear.

FIGS. 2A-2B illustrate a monitoring device that can be positioned withinan ear of a subject, according to some embodiments of the presentinvention.

FIG. 3A illustrates a monitoring device that can be positioned around anappendage of the body of a subject, according to some embodiments of thepresent invention.

FIG. 3B is a cross sectional view of the monitoring device of FIG. 3A.

FIG. 4 is a block diagram of a monitoring device according to someembodiments of the present invention.

FIG. 5 is a block diagram of a monitoring device according to someembodiments of the present invention.

FIGS. 6, 7A-7B, and 8-20 are flowcharts of operations for monitoring asubject according to embodiments of the present invention.

FIG. 21A is a graph illustrating two plots of real-time RRi (R-Rinterval) measurements taken from two different subjects wearing a PPGsensor during a period of 240 seconds: 60 seconds sitting in a chair, 60seconds standing in place, 60 seconds fast walking, and 60 seconds ofeasy walking.

FIG. 21B is a table which illustrates various calculated statisticalmetrics for the plots of the two subjects of FIG. 21A at three differentpolling and sampling frequencies (250 Hz, 125 Hz, and 25 Hz).

DETAILED DESCRIPTION

The present invention will now be described more fully hereinafter withreference to the accompanying figures, in which embodiments of theinvention are shown. This invention may, however, be embodied in manydifferent forms and should not be construed as limited to theembodiments set forth herein. Like numbers refer to like elementsthroughout. In the figures, certain layers, components or features maybe exaggerated for clarity, and broken lines illustrate optionalfeatures or operations unless specified otherwise. In addition, thesequence of operations (or steps) is not limited to the order presentedin the figures and/or claims unless specifically indicated otherwise.Features described with respect to one figure or embodiment can beassociated with another embodiment or figure although not specificallydescribed or shown as such.

It will be understood that when a feature or element is referred to asbeing “on” another feature or element, it can be directly on the otherfeature or element or intervening features and/or elements may also bepresent. In contrast, when a feature or element is referred to as being“directly on” another feature or element, there are no interveningfeatures or elements present. It will also be understood that, when afeature or element is referred to as being “secured”, “connected”,“attached” or “coupled” to another feature or element, it can bedirectly secured, directly connected, attached or coupled to the otherfeature or element or intervening features or elements may be present.In contrast, when a feature or element is referred to as being “directlysecured”, “directly connected”, “directly attached” or “directlycoupled” to another feature or element, there are no interveningfeatures or elements present. Although described or shown with respectto one embodiment, the features and elements so described or shown canapply to other embodiments.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. As used herein, the terms “comprise”, “comprising”,“comprises”, “include”, “including”, “includes”, “have”, “has”,“having”, or variants thereof are open-ended, and include one or morestated features, integers, elements, steps, components or functions butdoes not preclude the presence or addition of one or more otherfeatures, integers, elements, steps, components, functions or groupsthereof. Furthermore, as used herein, the common abbreviation “e.g.”,which derives from the Latin phrase “exempli gratia,” may be used tointroduce or specify a general example or examples of a previouslymentioned item, and is not intended to be limiting of such item. Thecommon abbreviation “i.e.”, which derives from the Latin phrase “idest,” may be used to specify a particular item from a more generalrecitation.

As used herein, the term “and/or” includes any and all combinations ofone or more of the associated listed items and may be abbreviated as“/”.

As used herein, phrases such as “between X and Y” and “between about Xand Y” should be interpreted to include X and Y. As used herein, phrasessuch as “between about X and Y” mean “between about X and about Y.” Asused herein, phrases such as “from about X to Y” mean “from about X toabout Y.”

Spatially relative terms, such as “under”, “below”, “lower”, “over”,“upper” and the like, may be used herein for ease of description todescribe one element or feature's relationship to another element(s) orfeature(s) as illustrated in the figures. It will be understood that thespatially relative terms are intended to encompass differentorientations of the device in use or operation in addition to theorientation depicted in the figures. For example, if a device in thefigures is inverted, elements described as “under” or “beneath” otherelements or features would then be oriented “over” the other elements orfeatures. Thus, the exemplary term “under” can encompass both anorientation of over and under. The device may be otherwise oriented(rotated 90 degrees or at other orientations) and the spatially relativedescriptors used herein interpreted accordingly. Similarly, the terms“upwardly”, “downwardly”, “vertical”, “horizontal” and the like are usedherein for the purpose of explanation only unless specifically indicatedotherwise.

It will be understood that although the terms first and second are usedherein to describe various features or elements, these features orelements should not be limited by these terms. These terms are only usedto distinguish one feature or element from another feature or element.Thus, a first feature or element discussed below could be termed asecond feature or element, and similarly, a second feature or elementdiscussed below could be termed a first feature or element withoutdeparting from the teachings of the present invention.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this invention belongs. It will befurther understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the specification andrelevant art and should not be interpreted in an idealized or overlyformal sense unless expressly so defined herein. Well-known functions orconstructions may not be described in detail for brevity and/or clarity.

The term “about”, as used herein with respect to a value or number,means that the value or number can vary more or less, for example by+/−20%, +/−10%, +/−5%, +/−1%, +/−0.5%, +/−0.1%, etc.

The terms “sensor”, “sensing element”, and “sensor module”, as usedherein, are interchangeable and refer to a sensor element or group ofsensor elements that may be utilized to sense information, such asinformation (e.g., physiological information, body motion, etc.) fromthe body of a subject and/or environmental information in a vicinity ofthe subject. A sensor/sensing element/sensor module may comprise one ormore of the following: a detector element, an emitter element, aprocessing element, optics, mechanical support, supporting circuitry,and the like. Both a single sensor element and a collection of sensorelements may be considered a sensor, a sensing element, or a sensormodule.

The term “optical emitter”, as used herein, may include a single opticalemitter and/or a plurality of separate optical emitters that areassociated with each other.

The term “optical detector”, as used herein, may include a singleoptical detector and/or a plurality of separate optical detectors thatare associated with each other.

The term “wearable sensor module”, as used herein, refers to a sensormodule configured to be worn on or near the body of a subject.

The terms “monitoring device” and “biometric monitoring device”, as usedherein, are interchangeable and include any type of device, article, orclothing that may be worn by and/or attached to a subject and thatincludes at least one sensor/sensing element/sensor module. Exemplarymonitoring devices may be embodied in an earpiece, a headpiece, a fingerclip, a digit (finger or toe) piece, a limb band (such as an arm band orleg band), an ankle band, a wrist band, a nose piece, a sensor patch,eyewear (such as glasses or shades), apparel (such as a shirt, hat,underwear, etc.), a mouthpiece or tooth piece, contact lenses, or thelike.

The term “monitoring” refers to the act of measuring, quantifying,qualifying, estimating, sensing, calculating, interpolating,extrapolating, inferring, deducing, or any combination of these actions.More generally, “monitoring” refers to a way of getting information viaone or more sensing elements. For example, “blood health monitoring”includes monitoring blood gas levels, blood hydration, andmetabolite/electrolyte levels.

The term “headset”, as used herein, is intended to include any type ofdevice or earpiece that may be attached to or near the ear (or ears) ofa user and may have various configurations, without limitation. Headsetsincorporating optical sensor modules, as described herein, may includemono headsets (a device having only one earbud, one earpiece, etc.) andstereo headsets (a device having two earbuds, two earpieces, etc.),earbuds, hearing aids, ear jewelry, face masks, headbands, and the like.In some embodiments, the term “headset” may include broadly headsetelements that are not located on the head but are associated with theheadset. For example, in a “medallion” style wireless headset, where themedallion comprises the wireless electronics and the headphones areplugged into or hard-wired into the medallion, the wearable medallionwould be considered part of the headset as a whole. Similarly, in somecases, if a mobile phone or other mobile device is intimately associatedwith a plugged-in headphone, then the term “headset” may refer to theheadphone-mobile device combination. The terms “headset” and “earphone”,as used herein, are interchangeable.

The term “physiological” refers to matter or energy of or from the bodyof a creature (e.g., humans, animals, etc.). In embodiments of thepresent invention, the term “physiological” is intended to be usedbroadly, covering both physical and psychological matter and energy ofor from the body of a creature.

The term “body” refers to the body of a subject (human or animal) thatmay wear a monitoring device, according to embodiments of the presentinvention.

The term “processor” is used broadly to refer to a signal processor orcomputing system or processing or computing method which may belocalized or distributed. For example, a localized signal processor maycomprise one or more signal processors or processing methods localizedto a general location, such as to a wearable device. Examples of suchwearable devices may comprise an earpiece, a headpiece, a finger clip, adigit (finger or toe) piece, a limb band (such as an arm band or legband), an ankle band, a wrist band, a nose piece, a sensor patch,eyewear (such as glasses or shades), apparel (such as a shirt, hat,underwear, etc.), a mouthpiece or tooth piece, contact lenses, or thelike. Examples of a distributed processor comprise “the cloud”, theinternet, a remote database, a remote processor computer, a plurality ofremote processors or computers in communication with each other, or thelike, or processing methods distributed amongst one or more of theseelements. The key difference is that a distributed processor may includedelocalized elements, whereas a localized processor may workindependently of a distributed processing system. As a specific example,microprocessors, microcontrollers, ASICs (application specificintegrated circuits), analog processing circuitry, or digital signalprocessors are a few non-limiting examples of physical signal processorsthat may be found in wearable devices.

The term “remote” does not necessarily mean that a remote device is awireless device or that it is a long distance away from a device incommunication therewith. Rather, the term “remote” is intended toreference a device or system that is distinct from another device orsystem or that is not substantially reliant on another device or systemfor core functionality. For example, a computer wired to a wearabledevice may be considered a remote device, as the two devices aredistinct and/or not substantially reliant on each other for corefunctionality. However, any wireless device (such as a portable device,for example) or system (such as a remote database for example) isconsidered remote to any other wireless device or system.

The terms “signal analysis frequency” and “signal sampling rate”, asused herein, are interchangeable and refer to the number of samples persecond (or per other unit) taken from a continuous sensor (i.e.,physiological sensor and environmental sensor) signal to ultimately makea discrete signal.

The term “sensor module interrogation power”, as used herein, refers tothe amount of electrical power required to operate one or more sensors(i.e., physiological sensors and environmental sensors) of a sensormodule and/or any processing electronics or circuitry (such asmicroprocessors and/or analog processing circuitry) associatedtherewith. Examples of decreasing the sensor interrogation power mayinclude lowering the voltage or current through a sensor element (suchas lowering the voltage or current applied to a pair of electrodes),lowering the polling (or polling rate) of a sensor element (such aslowering the frequency at which an optical emitter is flashed on/off ina PPG sensor), lowering the sampling frequency of a stream of data (suchas lowering the sampling frequency of the output of an optical detectorin a PPG sensor), selecting a lower-power algorithm (such as selecting apower-efficient time-domain processing method for measuring heart ratevs. a more power-hungry frequency-domain processing method), or thelike. Lowering the interrogation power may also include powering onlyone electrode, or powering less electrodes, in a sensor module or sensorelement such that less total interrogation power is exposed to the bodyof a subject. For example, lowering the interrogation power of a PPGsensor may comprise illuminating only one light-emitting diode ratherthan a plurality of light-emitting diodes that may be present in thesensor module, and lowering the interrogation power of a bioimpedancesensor may comprise powering only one electrode pair rather than aplurality of electrodes that may be present in the bioimpedance sensormodule.

The term “polling” typically refers to controlling the intensity of anenergy emitter of a sensor or to the “polling rate” and/or duty cycle ofan energy emitter element in a sensor, such as an optical emitter in aPPG sensor or an ultrasonic driver in an ultrasonic sensor. Polling mayalso refer to the process of collecting and not collecting sensor dataat certain periods of time. For example, a PPG sensor may be “polled” bycontrolling the intensity of one or more optical emitters, i.e. bypulsing the optical emitter over time. Similarly, the detector of a PPGsensor may be polled by reading data from that sensor only at a certainpoint in time or at certain intervals, i.e., as in collecting data fromthe detector of a PPG sensor for a brief period during each opticalemitter pulse. A sensor may also be polled by turning on or off one ormore elements of that sensor in time, such as when a PPG sensor ispolled to alternate between multiple LED wavelengths over time or whenan ultrasonic sensor is polled to alternate between mechanical vibrationfrequencies over time.

The terms “sampling frequency”, “signal analysis frequency”, and “signalsampling rate”, as used herein, are interchangeable and refer to thenumber of samples per second (or per other unit) taken from a continuoussensor or sensing element (for example, the sampling rate of thethermopile output in a tympanic temperature sensor).

It should be noted that processes for managing hysteresis are impliedherein. Namely, several embodiments herein for controlling sensors (andother wearable hardware) may involve a processor sending commands to asensor element depending on the sensor readings. Thus, in someembodiments, a sensor reading (such as a reading from an opticaldetector or a sensing electrode) above X may result in a processorsending a command to electrically bias another sensor element (such asan optical emitter or a biasing electrode) above Y. Similarly, as soonas the sensor reading drops below X, a processor may send a command tobias another sensor element below Y. However, in borderline situationsthis may cause unwanted hysteresis in the biasing command, as sensorreadings may rapidly toggle above/below X resulting in the toggling ofthe biasing of another sensor element above/below Y. As such, hysteresismanagement may be integrated within the algorithm(s) for controlling theexecution of a processor. For example, the processor may be configuredby the algorithm to delay a biasing command by a period of time Zfollowing the timing of a prior biasing command, thereby preventing orreducing the aforementioned toggling.

In the following figures, various monitoring devices will be illustratedand described for attachment to the ear or an appendage of the humanbody. However, it is to be understood that embodiments of the presentinvention are not limited to those worn by humans.

The ear is an ideal location for wearable health and environmentalmonitors. The ear is a relatively immobile platform that does notobstruct a person's movement or vision. Monitoring devices located at anear have, for example, access to the inner-ear canal and tympanicmembrane (for measuring core body temperature), muscle tissue (formonitoring muscle tension), the pinna, earlobe, and elsewhere (formonitoring blood gas levels), the region behind the ear (for measuringskin temperature and galvanic skin response), and the internal carotidartery (for measuring cardiopulmonary functioning), etc. The ear is alsoat or near the point of exposure to: environmental breathable toxicantsof interest (volatile organic compounds, pollution, etc.); noisepollution experienced by the ear; and lighting conditions for the eye.Furthermore, as the ear canal is naturally designed for transmittingacoustical energy, the ear provides a good location for monitoringinternal sounds, such as heartbeat, breathing rate, and mouth motion.

Optical coupling into the blood vessels of the ear may vary betweenindividuals. As used herein, the term “coupling” refers to theinteraction or communication between excitation energy (such as light)entering a region and the region itself. For example, one form ofoptical coupling may be the interaction between excitation lightgenerated from within an optical sensor of an earbud (or other devicepositioned at or within an ear) and the blood vessels of the ear. In oneembodiment, this interaction may involve excitation light entering theear region and scattering from a blood vessel in the ear such that thetemporal change in intensity of scattered light is proportional to atemporal change in blood flow within the blood vessel. Another form ofoptical coupling may be the interaction between excitation lightgenerated by an optical emitter within an earbud and a light-guidingregion of the earbud. Thus, an earbud with integrated light-guidingcapabilities, wherein light can be guided to multiple and/or selectregions along the earbud, can assure that each individual wearing theearbud will generate an optical signal related to blood flow through theblood vessels. Optical coupling of light to a particular ear region ofone person may not yield photoplethysmographic signals for each person.Therefore, coupling light to multiple regions may assure that at leastone blood-vessel-rich region will be interrogated for each personwearing an earbud. Coupling multiple regions of the ear to light mayalso be accomplished by diffusing light from a light source within anearbud.

According to some embodiments of the present invention, “smart”monitoring devices including, but not limited to, armbands and earbuds,are provided that change signal analysis frequency and/or sensor moduleinterrogation power in response to detecting a change in subjectactivity, a change in environmental conditions, a change in time, achange in location of the subject and/or a change in stress level of thesubject.

FIGS. 2A-2B illustrate a monitoring apparatus 20 configured to bepositioned within an ear of a subject, according to some embodiments ofthe present invention. The illustrated apparatus 20 includes an earpiecebody or housing 22, a sensor module 24, a stabilizer 25, and a soundport 26. When positioned within the ear of a subject, the sensor module24 has a region 24 a configured to contact a selected area of the ear.The illustrated sensor region 24 a is contoured (i.e., is “form-fitted”)to matingly engage a portion of the ear between the anti tragus andacoustic meatus, and the stabilizer is configured to engage theanti-helix. However, monitoring devices in accordance with embodimentsof the present invention can have sensor modules with one or moreregions configured to engage various portions of the ear. Various typesof device configured to be worn at or near the ear may be utilized inconjunction with embodiments of the present invention.

FIGS. 3A-3B illustrate a monitoring apparatus 30 in the form of a sensorband 32 configured to be secured to an appendage (e.g., an arm, wrist,hand, finger, toe, leg, foot, neck, etc.) of a subject. The band 32includes a sensor module 34 on or extending from the inside surface 32 aof the band 32. The sensor module 34 is configured to detect and/ormeasure physiological information from the subject and includes a sensorregion 34 a that is contoured to contact the skin of a subject wearingthe apparatus 30.

Embodiments of the present invention may be utilized in various devicesand articles including, but not limited to, patches, clothing, etc.Embodiments of the present invention can be utilized wherever PPG andblood flow signals can be obtained and at any location on the body of asubject. Embodiments of the present invention are not limited to theillustrated monitoring devices 20, 30 of FIGS. 2A-2B and 3A-3B.

The sensor modules 24, 34 for the illustrated monitoring devices 20, 30of FIGS. 2A-2B and 3A-3B are configured to detect and/or measurephysiological information from a subject wearing the monitoring devices20, 30. In some embodiments, the sensor modules 24, 34 may be configuredto detect and/or measure one or more environmental conditions in avicinity of the subject wearing the monitoring devices 20, 30.

A sensor module utilized in accordance with embodiments of the presentinvention may be an optical sensor module that includes at least oneoptical emitter and at least one optical detector. Exemplary opticalemitters include, but are not limited to light-emitting diodes (LEDs),laser diodes (LDs), compact incandescent bulbs, micro-plasma emitters,IR blackbody sources, or the like. In addition, a sensor module mayinclude various types of sensors including and/or in addition to opticalsensors. For example, a sensor module may include one or more inertialsensors (e.g., an accelerometer, piezoelectric sensor, vibration sensor,photoreflector sensor, etc.) for detecting changes in motion, one ormore thermal sensors (e.g., a thermopile, thermistor, resistor, etc.)for measuring temperature of a part of the body, one or more electricalsensors for measuring changes in electrical conduction, one or more skinhumidity sensors, and/or one or more acoustical sensors.

Referring to FIG. 4, a monitoring device (e.g., monitoring devices 20,30), according to embodiments of the present invention, includes atleast one processor 40 that is coupled to the sensor(s) of a sensormodule 24, 34 and that is configured to receive and analyze signalsproduced by the sensor(s). Collectively, the elements of FIG. 4 presenta system for intelligently controlling power consumption in a wearablemonitor, such as monitoring devices 20, 30.

The processor 40 is configured to change signal analysis frequencyand/or sensor module interrogation power in response to detecting achange in activity of a subject wearing the monitoring device. Forexample, in some embodiments, the processor 40 increases signal analysisfrequency and/or sensor module interrogation power in response todetecting an increase in subject activity, and decreases signal analysisfrequency and/or sensor module interrogation power in response todetecting a decrease in subject activity. In other embodiments, theprocessor 40 implements frequency-domain digital signal processing inresponse to detecting high subject activity (e.g., the subject startsrunning, exercising, etc.), and implements time-domain digital signalprocessing in response to detecting low subject activity. The frequency-and time-domain algorithms represent two different signal extractionmethods for extracting accurate biometrics from optical sensor signals,where the frequency-domain algorithm may require substantially greaterprocessing power than that of the time-domain algorithm. The reason thatfrequency-domain algorithms may require more power is because spectraltransforms may be employed, whereas time-domain algorithms may employlower-power filters and pulse picking.

An analysis platform 50 may be in communication with the processor 40and a memory storage location 60 for the algorithms. The analysisplatform 50 may be within a wearable device (e.g., monitoring devices20, 30) or may be part of a remote system in wireless or wiredcommunication with the wearable device. The analysis platform 50 mayanalyze data generated by the processor 40 to generate assessments basedon the data. For example, the analysis platform 50 may analyze vitalsign data (such as heart rate, respiration rate, RRi, blood pressure,etc.) in context of the user's activity data to assess a health orfitness status of the person, such as a health or fitness score. In aspecific example of such an assessment, the analysis platform 50 mayassess a subject's VO₂ max (maximum volume of oxygen consumption) by: 1)identifying data where the subject walked at a speed (as measured by amotion sensor) less than a threshold value (for example, 2.5 mph), 2)selectively analyzing the breathing rate (as measured by a physiologicalsensor) for this selected data (for example, by taking an average valueof the selected breathing rate data and inverting it to get 1/breathingrate), and 3) generating a fitness assessment (such as a VO₂ maxassessment) by multiplying the inverted value by a scalar value. Anumber of assessments can be made by analyzing physiological and motion(activity) data, and this is only a specific example.

It should be noted that, herein, the steps described wherein theprocessor 40 is used to make a determination or decision may beinterchanged with the analysis platform 50 instead, as the analysisplatform may be configured to have the same features as the processor 40itself. For example, if the processor 40 determines that a subject's VO₂max is too high, via an algorithm, the analysis platform 50 may also beconfigured to assess this determination. Thus, in some embodiments, theanalysis platform 50 may be configured such that a processor 40 is notneeded, such as the case where a sensor of a sensor module (e.g., sensormodule 24, 34) is in wireless communication directly with a remoteanalysis platform 50.

The analysis platform 50 may be configured to analyze data processed bythe processor 40 to assess the efficacy (or confidence value) of thealgorithms used by the processor 40 and to autonomously modify thealgorithms to improve the acuity of the wearable monitoring device. Forexample, the processer 40 may be configured to generate a confidencescore for a given metric. The confidence score may be an indication ofhow strongly a processed metric may be trusted. For example,signal-to-noise (S/N) ratio may be processed from a PPG signal byassessing the AC amplitude of the blood flow waveform to a noise value,and a low S/N may represent a low confidence. If the analysis platform50 determines that confidence value for a given algorithm is low, it mayadjust the algorithm for future processing events implemented by theprocessor 40. For example, the algorithm may be changed such that athreshold may be lowered; as a specific example, the activity thresholdfor raising the signal analysis frequency and/or sensor moduleinterrogation power may be lowered such that the acuity of the wearablesensor increases during activity. In some embodiments, the analysisplatform 50 may determine that an entirely different algorithm must beused for processing, and a replacement algorithm may be selected viacommand from the analysis platform 50. In some embodiments, thisreplacement algorithm may be associated with a given confidence valuerange, and the analysis platform 50 may select the replacement algorithmbased on the determined confidence value. For example, if the analysisplatform 50 determines that the confidence value of one algorithm is toolow for a user, the analysis platform may automatically replace thealgorithm with another algorithm that provides higher confidence.However, other methods may be used to select an algorithm forimplementation by the processor 40 based on a confidence determination,in accordance with some embodiments of the present invention.

In the case where the sensor module (or modules) comprises PPG sensorfunctionality, readings from the sensor module (for example, readingsfrom optical sensors or motion sensors) can be used to trigger changesto the optomechanical engine (the optical emitter, detector, andassociated optics). For example, the detection of low activity maychange the polling of the optomechanical engine. In a specific example,a detection of low activity may change the optical wavelength used forPPG. In this example, if the activity level processed by the processor40 is deemed to be “low”, the primary wavelength of detection may shiftfrom visible (such as green or yellow) wavelengths to infraredwavelengths. This can be useful for automatically turning off visibleemitters when the person is rested, helping to prevent visible lightpollution so that the person can sleep better.

For example, in one embodiment, the processor 40 and/or analysisplatform may determine that the person is sleeping, and then the actionof changing wavelengths may be initiated by the processor 40 (i.e., viaa command to the PPG sensor). This may be achieved by the processorand/or analytics engine processing activity and/or physiological dataagainst a threshold criteria (i.e., processing accelerometer data todetermine a state of low enough physical activity and that the person islaying flat/parallel to the ground) and/or physiological model (i.e.,processing PPG sensor information to determine that the person'sbreathing, heart rate, and/or HRV is of a pattern associated withsleeping) to determine that the person is sleeping. Alternatively, theprocessor and/or analytics platform may automatically determine that theperson is in a dark environment (i.e., by processing optical sensor datato determine that the person is in a dark enough environment) and thensend a command to switch change the wavelengths of the PPG sensor. Inanother embodiment, the user may manually initiate a command (i.e., bypressing a button) that the person is going to sleep, which my then beused by the processor and/or analysis platform to change thewavelengths. Also, although the PPG S/N ratio for infrared (IR)wavelengths may be less than that for visible wavelengths, the totalelectrical power levels (i.e., the bias voltage) required to bias the IRemitter may be lower, thereby saving battery life in conditions of lowactivity.

This approach may also be used for pulse oximetry via a PPG sensor. Forexample, the processor 40 may process sensor readings from a sensormodule 24, 34 to determine that the subject wearing the wearable deviceis indoors or outdoors, and the processor 40 may select a differentoptomechanical polling routine for indoors vs. outdoors. For example,when indoors, a visible and IR emitter may be engaged to facilitate SpO₂determination. But once the user is outdoors, where visible outdoorlight may pollute PPG sensor readings with noise signals too intense toremove with physical or digital optical filters, the processor mayengage (poll) multiple IR emitters instead of the visible and IRemitter, and SpO₂ determination may be executed via two IR wavelengthbands rather than a visible+IR wavelength band. For example, theprocessor 40 may turn off visible emitters when the user is outdoors andmay turn on multiple IR emitters, such as a ˜700 nm and ˜940 nm emitter,instead. Because pulse oximetry requires two distinct wavelengths or twodifferent wavelength bands in order to generate an estimate of SpO2,these two IR wavelengths/wavelength bands may be used with efficacyoutdoors. The example of these two wavelengths/wavelength bands shouldnot be construed to be limiting, as various wavelength configurationsmore resilient to outdoor light contamination may be used, such asspectral bands in solar blind regions (wavelengths that are naturallyattenuated by the earth's atmosphere, such as ˜763 nm and others).Additionally, it should be noted that monitoring blood oxygen (SpO2) andtissue oxygen may each be achieved via this method, depending on thesensor positioning used. For example, locating a PPG sensor at a leg orarm may facilitate a more accurate determination of muscle oxygenation,whereas locating a PPG sensor at a finger, ear, or forehead may befacilitate a more accurate determination of blood oxygenation. Moreover,the muscle oxygenation signals collected may be used as a proxy forestimating lactic acid and/or lactate threshold (or anaerobic threshold)in the muscle of the subject, as oxygen depletion may be correlated withhigher lactic acid build-up in the muscles.

Besides the example just described, autonomously triggering changes inthe optomechanical engine of a PPG sensor, in response to activity datasensed by an activity (motion) sensor, can be applied towards a numberof useful functions. For example, the detection of low activity maychange the type of PPG-based measurement to be executed. This can beuseful for cases where the accuracy of a physiological measurement orassessment demands a certain level of physical activity or inactivity.As a specific example, a measurement of blood pressure or RRi (R-Rinterval, which is the interval from the peak of one QRS complex to thepeak of the next as shown on an electrocardiogram) may provide bestresults during periods of inactivity. The processor 40 may deem thatactivity is “low enough” to execute one or more of such measurements,and then execute an algorithm to start measuring. This way, bloodpressure and/or RRi measurements are only executed at time periods wherea reliable measurement can be made, thereby saving system power.Similarly, in some embodiments, a measurement of HRR (heart raterecovery) may be executed only when the processor 40 deems that activity“high enough” to make such a measurement meaningful. For example, theprocessor 40 may determine that a user's activity level (perhaps assensed by an activity sensor) or exertion level (perhaps as sensed by aheart rate sensor) has been high enough for a long enough period oftime, followed by a resting phase, such that HRR may be accuratelyassessed. In this case, several data points of activity level and/orheart rate may be stored in memory or buffered, such that the processor40 may run through the dataset to determine if the user has been in astate of high activity or exertion for a long enough period of time tojustify an HRR measurement. This way, HRR measurements are only executedat time periods where a reliable measurement can be made, saving powerconsumption.

In another example, if the processor 40 determines that subject activitylevel has been very low, the processor 40 may engage a longer wavelengthlight, such as IR light, as the wavelength for PPG. But if subjectactivity is heightened, the processor 40 may switch the wavelength to ashorter wavelength, such as green, blue, or violet light. Such a processmay address the problem of low perfusion, which often prevents PPGreadings during periods of subject inactivity, especially forwrist-based PPG sensors. Shorter wavelength light for PPG generallyyields a higher signal-to-noise ratio (S/N) over longer wavelength, butlow perfusion can reduce blood flow at the surface of the skin, pushingblood flow so far below the surface that shorter wavelength light isabsorbed by the skin before reaching blood flow. However, duringexercise, perfusion may return and shorter wavelength light may be usedonce again, providing a higher S/N for PPG and thereby reducing systempower requirements.

In another example, if the processor 40 determines that subjectperfusion is low, for example by processing PPG information to determinethat the signal-to-noise level is quite low, the processor 40 may send acommand to the sensor module 24, 34 to raise the localized temperatureof the neighboring skin, thereby increasing perfusion. This may beachieved by the processor 40 sending a command to turn on a heaterelement on the sensor module 24, 34 or to increase the electrical biasacross an LED such that the LED heats up the skin to encourage bloodflow. Once the signal-to-noise level is determined to be high enough foraccurate and reliable physiological monitoring by the processor 40, theprocessor 40 may send a command to terminate heating of the skin.

For the case of PPG sensor modules 24, 34 in the system of FIG. 4, thereare certain wavelengths of light that may be better for sensing specificbiometric parameters. For example, whereas IR or green light may be bestfor sensing heart rate-related modulations in blood flow, blue or violetlight may be best for sensing respiration-related modulations in bloodflow. Thus, in some embodiments of the present invention, the processor40 may be configured to select a given PPG wavelength routinely in time,according to an algorithm 60, such that various parameters are measuredsequentially in time order rather than being measured simultaneously ina continuous fashion. In this way, various wavelengths of light can beturned on and off at different periods in time in order to measurevarious biometric parameters in sequence.

Readings from sensor module(s) can also be used to trigger a change inthe algorithm sequence executed by a processor 40. For example if anormal heart rate level and/or heart rate variability (HRV) level isdetected by the processor (such as a heart rate and/or HRV within aspecified range), then the processor 40 may select an algorithm that hasless sequential steps in time, thus saving power on the processor 40.More specifically, once an abnormal heart rate and/or HRV is detectedoutside the specified range, the processor 40 may select an algorithmthat also implements continuous cardiac monitoring, such as monitoringof arrhythmia, atrial fibrillation, blood pressure, cardiac output,irregular heart beats, etc. And when heart rate and/or HRV fall backwithin the specified range, the processor 40 may return to a lower-poweralgorithm with less sequential steps in time.

Readings from the sensor(s) of a monitoring device can be used totrigger events. In addition, sensor signals may be processed andalgorithms may be selected to control a biometric signal extractionmethod. For example, elevated subject physical activity sensed by anaccelerometer may trigger a change in the signal extraction algorithmfor PPG towards one of higher acuity (but higher power usage); then,when subject activity winds down, the algorithm may change to one thatis lower acuity (but lower power usage). In this way, battery power maybe preserved for use cases where high acuity is not needed (such assedentary behavior where motion artifacts need not be removed.)

In some embodiments, detecting a change in subject activity comprisesdetecting a change in at least one subject vital sign, such as subjectheart rate, subject blood pressure, subject temperature, subjectrespiration rate, subject perspiration rate, etc. In other embodiments,the sensor module includes a motion sensor, such as an accelerometer,gyroscope, etc., and detecting a change in subject activity includesdetecting a change in subject motion via the motion sensor.

According to some embodiments, the type of activity may be identified orpredicted via the processor 40. Changing signal analysis frequencyand/or sensor module interrogation power may be based on stored profiles(such as a look-up table) or learned profiles (such as machine learningwith human input) of activity identification information, such as: 1) aknown accelerometry profile for a given sport or exercising activityand/or 2) a known accelerometry profile for a particular person, forexample.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject, such as monitoringdevices 20, 30, includes a sensor module configured to detect and/ormeasure physiological information from the subject and to detect and/ormeasure at least one environmental condition in a vicinity of thesubject. The sensor module may be an optical sensor module that includesat least one optical emitter and at least one optical detector, althoughvarious other types of sensors may be utilized. A processor 40 iscoupled to the sensor module and is configured to receive and analyzesignals produced by the sensor module. In addition, the processor 40 isconfigured to change signal analysis frequency and/or sensor moduleinterrogation power in response to detecting a change in the at leastone environmental condition. Exemplary changes in environmentalconditions include changes in one or more of the following ambientconditions: temperature, humidity, air quality, barometric pressure,radiation, light intensity, and sound. In some embodiments, theprocessor 40 increases signal analysis frequency and/or sensor moduleinterrogation power in response to detecting an increase in the at leastone environmental condition, and decreases signal analysis frequencyand/or sensor module interrogation power in response to detecting adecrease in the at least one environmental condition. For example, thesignal analysis frequency and/or sensor module interrogation power maybe increased when air quality worsens or becomes detrimental to thewearer, and signal analysis frequency and/or sensor module interrogationpower may be decreased when air quality improves. The principle behindthis process is that extreme or harsh ambient changes in environment(such as extreme hot or cold, extreme humidity or dryness, etc.) maylower the S/N ratio of the processed signals. Thus, higher processingpower may be required to actively remove noise.

Referring to FIG. 5, according to other embodiments of the presentinvention, a monitoring device configured to be attached to a subject,such as monitoring devices 20, 30, includes a clock 82 (or is incommunication with a clock 82), a sensor module 24, 34 configured todetect and/or measure physiological information from the subject (and/orenvironmental condition information in a vicinity of the subject), and aprocessor 40 coupled to the clock 82 and the sensor module. The sensormodule 24, 34 may be an optical sensor module that includes at least oneoptical emitter and at least one optical detector, although variousother types of sensors may be utilized. The processor 40 is configuredto receive and analyze signals produced by the sensor module 24, 34, andis configured to change signal analysis frequency and/or changes sensormodule interrogation power at one or more predetermined times.

In some embodiments, the processor 40 increases signal analysisfrequency and/or sensor module interrogation power at a first time, anddecreases signal analysis frequency and/or sensor module interrogationpower at a second time. For example, signal analysis frequency and/orsensor module interrogation power may be increased at a particular timeof day (e.g., the time of day when the wearer is typically exercising),and may be decreased at another time of day, for example, at a time ofday when the wearer is less active (e.g., nighttime, etc.).

In other embodiments, the processor 40 adjusts signal analysis frequencyand/or sensor module interrogation power according to a circadian rhythmof the subject. For example, signal analysis frequency and/or sensormodule interrogation power may be increased at a particular time of day(e.g., the time of day when the wearer is at peak metabolism), and maybe decreased at another time of day (for example, during sleep).

In other embodiments, the processor 40 adjusts signal analysis frequencyand/or interrogation power of a sensor module 24, 34 or analysisplatform 50 based on the determined stress state of the user. Forexample, the processor 40 may determine that a user is psychologicallystressed based on, for example, an elevated heart rate over a period oftime during low (not high) physical activity. The processor 40 may thensend a signal to another sensor and/or analysis platform, such as avoice analysis/recognition system 84 that is in communication with thesystem 90 of FIG. 4, to control the processing power of voicerecognition. In this manner, a more stressed psychological state mayresult in a higher processing power for the voice recognition system 84;in contrast, a low stress state may trigger lower power processingbecause it may be easier for the voice recognition system 84 tounderstand someone when they are calm rather than excited. As anotherexample, the processor 40 may identify a pattern of low heart rate byprocessing information from a heart rate sensor over a 25, period oftime; in response, the processor may lower the signal analysis frequencyand/or interrogation power performed in another simultaneousmeasurement, such as RRi (R-R interval). Though the sampling frequencymay be reduced for the RRi calculation in this example, RRi acuity maynot be sacrificed because lower heart rate implies generally longer R-Rintervals. Longer intervals do not require high sampling rates fordetection/measurement.

As yet another example, the processor 40 may adjust signal analysisfrequency and/or interrogation power of a user interface 70 that is incommunication with the system 90 of FIG. 4 (e.g., a user interface of atelecommunication device, such as a smartphone, computer, etc., or auser interface associated with a monitoring device 20, 30), based on thedetermined stress state of a subject wearing a monitoring device 20, 30.In this example, the processor 40 may determine that a user ispsychologically stressed and then send a signal (i.e., a command) to theuser interface 70, such as a view screen, such that the font size ofdisplayed text is increased and/or the screen brightness is increasedand/or an image displayed within the user interface 70 is easier toview/comprehend (e.g., increase the resolution of the image, etc.).Then, once the processor 40 determines that the subject's stress levelis sufficiently low, the processor 40 may signal a low-power mode ofoperation for the user interface 70, by lowering the screen brightnessand/font size of displayed text and/or reducing the resolution of adisplayed image(s), for example.

According to other embodiments of the present invention, a monitoringdevice configured to be attached to a subject, such as monitoringdevices 20, 30, includes a location sensor 80 (FIG. 5), a sensor module24, 34 configured to detect and/or measure physiological informationfrom the subject, and a processor 40 coupled to the location sensor 80and the sensor module 24, 34. The sensor module 24, 34 may be an opticalsensor module that includes at least one optical emitter and at leastone optical detector, although various other types of sensors may beutilized. The processor 40 is configured to receive and analyze signalsproduced by the sensor module 24, 34 and to change signal analysisfrequency and/or sensor module interrogation power when the locationsensor 80 indicates the subject has changed locations.

In some embodiments, the processor 40 increases signal analysisfrequency and/or sensor module interrogation power when the locationsensor 80 indicates the subject is at a particular location, anddecreases signal analysis frequency and/or sensor module interrogationpower when the location sensor 80 indicates the subject is no longer atthe particular location. For example, signal analysis frequency and/orsensor module interrogation power may be increased when the locationsensor 80 indicates the subject is at a particular location (e.g., atthe gym, outdoors, at the mall, etc.), and may be decreased when thelocation sensor 80 indicates the subject is no longer at the particularlocation (e.g., when the wearer is at work, home, etc.). The locationsselected for the increase or decrease in processing power may bepersonalized for the user and stored in memory. For example, people whoare more active at outdoors than at work may see the decision treedescribed above, but for those who are more active at work, the decisiontree may be swapped such that higher power processing is selected forwork locations over home locations.

Other factors may be utilized to trigger an increase or decrease insignal analysis frequency and/or sensor module interrogation power. Forexample, higher body temperature readings detected by a thermal sensorassociated with the sensor module 24, 34 may trigger changes in signalanalysis frequency and/or sensor module interrogation power. Theprinciple behind this may be that higher body temperatures areassociated with higher motion, for example. The detection of higherlight levels, the detection of higher changes in light intensity, and/orthe detection of particular wavelengths via an optical sensor associatedwith the sensor module 24, 34 may trigger changes in signal analysisfrequency and/or sensor module interrogation power. Lower potentialdrops detected by an electrical sensor associated with the sensor module24, 34 may trigger changes in signal analysis frequency and/or sensormodule interrogation power. Lower skin humidity readings detected via ahumidity sensor associated with the sensor module may trigger changes insignal analysis frequency and/or sensor module interrogation power.Higher acoustic noise levels detected via an acoustical sensorassociated with the sensor module 24, 34 may trigger changes in signalanalysis frequency and/or sensor module interrogation power.

Referring now to FIG. 6, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes a sensor module 24, 34 configured to detect and/ormeasure physiological information from the subject and a processor 40configured to receive and analyze signals produced by the sensor module.The subject is monitored for change in physical activity level (Block100). If a change is detected (Block 102), the processor 40 changessignal analysis frequency and/or sensor module interrogation power(Block 104).

As illustrated in FIG. 7A, changing signal analysis frequency and/orsensor module interrogation power (Block 104) may include increasingsignal analysis frequency and/or sensor module interrogation power inresponse to detecting an increase in subject activity (Block 106), anddecreasing signal analysis frequency and/or sensor module interrogationpower in response to detecting a decrease in subject activity (Block108). As described above, one method of lowering the interrogation poweris powering only one electrode, or powering less electrodes, in a sensormodule 24, 34 or sensor element such that less total interrogation poweris exposed to the body of a subject. For example, in response todetecting an increase in subject activity (Block 106), the system ofFIG. 4 may power only one optical emitter (or illuminate less opticalemitters) in the sensor module 24, 34, rather than a plurality ofoptical emitters that may be present in a wearable PPG module. Then,once high activity is detected, for example high activity detectedduring exercise, the system may return power to all of the opticalemitters (or more of the optical emitters) in the PPG module. Becauselow activity may require less light for accurate PPG monitoring whencompared with high physical activity, in the described manner, both highand low activity levels can result in accurate PPG measurements whilebalancing power requirements.

In other embodiments as illustrated in FIG. 7B, changing signal analysisfrequency and/or sensor module interrogation power (Block 104) mayinclude implementing frequency-domain digital signal processing inresponse to detecting an increase in subject activity (Block 110), andimplementing time-domain digital signal processing in response todetecting a decrease in subject activity (Block 112).

Referring now to FIG. 8, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes a sensor module 24, 34 configured to detect and/ormeasure physiological information from the subject and/or measure atleast one environmental condition in a vicinity of the subject, and aprocessor 40 coupled to the sensor module 24, 34 that is configured toreceive and analyze signals produced by the sensor module 24, 34. Thevicinity of the subject is monitored for changes in one or moreenvironmental conditions (Block 200). If a change is detected (Block202), the processor 40 changes signal analysis frequency and/or sensormodule interrogation power (Block 204). As illustrated in FIG. 9,changing signal analysis frequency and/or sensor module interrogationpower (Block 204) may include increasing signal analysis frequencyand/or sensor module interrogation power in response to detecting anincrease in an environmental condition (e.g., an increase intemperature, humidity, air pollution, light intensity, sound, etc.)(Block 206), and decreasing signal analysis frequency and/or sensormodule interrogation power in response to detecting a decrease in anenvironmental condition (e.g., a decrease in temperature, humidity, airpollution, light intensity, sound, etc.) (Block 208).

Referring now to FIG. 10, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes or is in communication with a clock 82, a sensor module24, 34 configured to detect and/or measure physiological informationfrom the subject, and a processor 40 coupled to the clock 82 and thesensor module 24, 34 that is configured to receive and analyze signalsproduced by the sensor module 24, 34. The processor 40 changes signalanalysis frequency and/or sensor module interrogation power at one ormore predetermined times (Block 300). For example, signal analysisfrequency and/or sensor module interrogation power is increased at afirst time (e.g., at a particular time of the day, week, etc.) (Block302) and signal analysis frequency and/or sensor module interrogationpower is decreased at a second time (e.g., another time of the day,week, etc.) (Block 304). In other embodiments, as illustrated in FIG.11, changing signal analysis frequency and/or sensor moduleinterrogation power at one or more predetermined times (Block 300)includes adjusting signal analysis frequency and/or sensor moduleinterrogation power according to a circadian rhythm of the subject(Block 306).

Referring now to FIG. 12, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes a location sensor 80 (or is in communication with alocation sensor 80), a sensor module 24, 34 configured to detect and/ormeasure physiological information from the subject, and a processor 40coupled to the location sensor 80 and the sensor module 24, 34 that isconfigured to receive and analyze signals produced by the sensor module24, 34. The subject is monitored for a change in location (Block 400).If a change is detected (Block 402), the processor 40 changes signalanalysis frequency and/or sensor module interrogation power (Block 204).As illustrated in FIG. 13, changing signal analysis frequency and/orsensor module interrogation power (Block 404) may include increasingsignal analysis frequency and/or sensor module interrogation power inresponse to detecting that the subject is at a particular location(Block 406), and decreasing signal analysis frequency and/or sensormodule interrogation power in response to detecting that the subject isno longer at the particular location (Block 408). For example, signalanalysis frequency and/or sensor module interrogation power may beincreased when it is detected that the subject is at the gym and signalanalysis frequency and/or sensor module interrogation power may bedecreased when it is detected that the subject has returned home.

Referring now to FIG. 14, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes a sensor module 24, 34 configured to detect and/ormeasure physiological information from the subject and a processorconfigured to receive and analyze signals produced by the sensor module24, 34. The sensor module 24, 34 includes at least one optical emitterand at least one optical detector. The subject is monitored for changein physical activity level (Block 500). If a change is detected (Block502), the processor 40 changes wavelength of light emitted by the atleast one optical emitter (Block 504).

As illustrated in FIG. 15, changing wavelength of light emitted by theat least one optical emitter (Block 504) may include emitting shorterwavelength light in response to detecting an increase in subjectactivity (Block 506), and emitting longer wavelength light in responseto detecting an decrease in subject activity (Block 508). Shorterwavelength light may be less susceptible to motion artifacts. Longerwavelength light may require less battery power and also may beinvisible to the eye and thus more appealing for long-term wear of awearable monitor.

Referring now to FIG. 16, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes a sensor module 24, 34 configured to detect and/ormeasure physiological information from the subject and a processor 40configured to receive and analyze signals produced by the sensor module24, 34. The sensor module 24, 34 includes at least one optical emitterand at least one optical detector. The sensor module 24, 34 emits light,via the at least one optical emitter, at one or more wavelengths duringeach of a series of respective time intervals (Block 600) to facilitatethe measurement of a variety of different physiological parameters ofthe subject in the respective time intervals via data collected by theat least one optical detector (Block 602).

For example, an algorithm may comprise a list of successive intervals,wherein each interval may comprise: 1) a different polling of theoptical emitter and/or detector and/or 2) a different interrogationwavelength or set of interrogation wavelengths. As a specific example,an algorithm may focus on collecting and/or processing information forthe measurement of heart rate, RRi, and blood pressure in order. In suchcase, the following intervals may be executed in series (in noparticular order): 1) calculate heart rate, 2) calculate RRi, 3)calculate blood pressure, and 4) calculate breathing rate. Heart ratemay be calculated with a processor-intensive calculation to activelyremove motion artifacts via a motion (noise) reference, such as footstepand body motion artifacts, as disclosed in U.S. Patent ApplicationPublication No. 2015/0018636, U.S. Patent Application Publication No.2015/0011898, U.S. Pat. No. 8,700,11, and U.S. Pat. No. 8,157,730, whichare incorporated herein by reference in their entireties.

RRi may be calculated via a time-domain approach, such as applying aprocessor-efficient peak-finder or by leveraging a heart rate feedbackfilter to improve RRi tracking, for example as disclosed in U.S. PatentApplication Publication No. 2014/0114147, which is incorporated hereinby reference in its entirety. Blood pressure may be calculated byprocessing the photoplethysmogram itself (e.g., via intensity, shape,1st derivative, 2nd derivative, integral, etc.) via aprocessor-efficient time-domain algorithm. Breathing rate (respirationrate) may be calculated by running the optical detector signal through alow-pass filter, in some cases by applying a variable feedback loop toalign the corner frequency with the heart rate, for example as disclosedin U.S. Patent Application Publication No. 2014/0114147.

In all four cases of this specific example, a different opticalwavelength (or a different set of wavelengths) may be used. For example,calculating heart rate may employ a variety of different wavelengths,but calculating breathing rate may employ shorter-wavelength light (suchas wavelengths shorter than 600 nm, or preferably shorter than 480 nm)such that heart rate PPG signals do not overpower breathing rate PPGsignals during processing of breathing rate. In the example just given,with 4-intervals of optical signal sampling, further power reductionscan be realized by an algorithm which selects which intervals to executedepending on the activity state of the user. For example, if theactivity state reaches a certain threshold, the algorithm may selectthat only the first and fourth intervals (the heart rate and breathingrate data collection intervals) are activated. Similarly, if theactivity state is below a certain threshold, the algorithm may selectthat only the second and third intervals (the RRi and blood pressureintervals) are activated. In this manner, only the physiologicalparameters that are relevant to a particular activity state may becalculated, thereby saving system power and increasing the battery lifeof the wearable monitoring device.

In some embodiments, the wavelength of the optical emitter and opticaldetector may stay the same for each interval, but in contrast thesampling and/or polling of the sensor element (i.e., the sampling of thedetector(s) and the polling of the emitter(s)) may be changed dependingon the measurement goal of each interval. For example, an algorithm mayfocus on processing at least one photoplethysmogram to measure orestimate 1) blood pressure (highest sampling and/or polling), 2) heartrate variability (2nd-higest sampling and/or polling), and 3) low-motion(“lifestyle”) heart rate monitoring (lowest sampling and/or polling) insequence. This may be because accurately assessing blood pressure from aphotoplethysmogram may require a higher data acuity, whereas accurateheart rate variability may require less acuity, and heart rate underlifestyle (low motion) conditions may require the least acuity. Inanother embodiment, the polling and/or sampling for blood pressure maybe greater than 125 Hz, the polling and/or sampling of HRV may bebetween 250 Hz and 100 Hz, and the polling and/or sampling of lifestyleheart rate may be less than 75

Hz.

In another embodiment, an algorithm may focus on processing at least onephotoplethysmogram to generate a single real-time biometric parameter atdifferent intervals, with each interval having a different pollingand/or sampling rate. As an example, an algorithm may process aphotoplethysmogram to generate RRi at various different intervals where,for each interval, the polling rate of the optical emitter and thesampling rate of the optical detector may be different. As a specificexample, there may be three intervals, each having an increasingly lowerpolling and/or sampling rate. The optimum sampling rate to maintainmeasurement accuracy while limiting power consumption has been found byexperiment, as shown in FIGS. 21A and 21B.

FIG. 21A presents two plots 800, 802 of real-time RRi measurements takenfrom two different subjects wearing a PPG sensor (e.g., monitoringdevices 20, 30) during a period of 240 seconds: 60 seconds sitting in achair, 60 seconds standing in place, 60 seconds fast walking, and 60seconds of easy walking. Plot 800 is of subject one and plot 802 is ofsubject two. Post analysis of these two datasets yields the table 810shown in FIG. 21B, which illustrates various calculated statisticalmetrics for the plots of subject one and subject two at three differentpolling and sampling frequencies (250 Hz, 125 Hz, and 25 Hz). It can beseen that the calculated median and mean values of RRi is nearlyidentical for all of the frequencies for each respective subject.However, the calculated values for SD (standard deviation) and NN50 (thenumber of pairs of successive R-R intervals, “NNs”, that differ bygreater than 50 milliseconds) are shown to be dependent on samplingfrequency. Thus, from FIG. 21B, in order to maintain measurementaccuracy while keeping power consumption low, it can be shown that anideal polling/sampling for the proposed three intervals may be ˜125 Hzfor the NN50 calculation, between 125 and 25 Hz for the SD calculation,and 25 Hz for a heart rate calculation during low physical activity(lifestyle conditions).

Referring now to FIG. 17, a method of monitoring a subject via amonitoring device, such as monitoring devices 20, 30, according to someembodiments of the present invention, will be described. The monitoringdevice includes a sensor module 24, 34 configured to detect and/ormeasure physiological information from the subject and a processor 40configured to receive and analyze signals produced by the sensor module24, 34. The subject is monitored for change in stress level (Block 700).If a change is detected (Block 702), the processor 40 changes signalanalysis frequency and/or sensor module interrogation power (Block 704).In some embodiments, if a change is detected, the measurement intervals(as described previously) may change. In some embodiments, if a changeis detected (Block 702), processing power to a voice recognition system84 associated with the monitoring device is changed (Block 706). In someembodiments, if a change is detected (Block 702), changes in appearanceare made to a user interface 70 associated with the monitoring device(Block 708).

If the system 90 of FIG. 4 determines that the subject is experiencing acertain level of stress, such as the subject having an elevated heartrate in context of low physical activity, the system 90 may increase thenumber of intervals and/or biometrics that are measured. For example,the system 90 may increase the number of measurement intervals orperiods of the intervals in order to assess multiple biometrics, such asrespiration rate, blood pressure, and RRi, for example. In this way, inresponse to an elevated state of subject stress, processing resourcesmay be increased in order to initiate a more thorough biometric analysisof the subject. In contrast, when the stress level is determined to besufficiently low, the system 90 may reduce the number of measurementintervals and/or reduce the number of biometrics being measured, such aslimiting the measurement to heart rate only, for example.

As illustrated in FIG. 18, changing signal analysis frequency and/orsensor module interrogation power (Block 704) may include increasingsignal analysis frequency and/or sensor module interrogation power inresponse to detecting an increase in subject stress level (Block 710),and decreasing signal analysis frequency and/or sensor moduleinterrogation power in response to detecting a decrease in subjectstress level (Block 712). As a specific example, of this embodiment, thealgorithm(s) 60 being executed by the processor 40 in the system 90 maybe configured to operate in a “screening mode” to analyze the overallstress (wellbeing or health) of a subject wearing a sensor module 24,34. When the processor determines that the stress reading is outside ofan acceptable range for the subject, the processor may then focus orincrease processing resource towards determining the origin of thestress condition. For example, the processor 40 may process PPG datafrom a sensor module 24, 34 to determine that a person is likely to haveatrial fibrillation, and upon this determination the processor mayincrease the frequency of the pulsing of the optical emitter(s) of a PPGsensor, and/or increase the sampling rate of the PPG sensor, to collecthigher acuity data for definitively diagnosing that atrial fibrillationis truly occurring.

As illustrated in FIG. 19, changing processing power to a voicerecognition system 84 may include increasing processing power for thevoice recognition system 84 in response to detecting an increase insubject stress level (Block 714), and decreasing processing power forthe voice recognition system 84 in response to detecting an decrease insubject stress level (Block 716). For example, if the system 90 of FIG.4 determines that the subject is experiencing a certain level of stress,such as the subject having a low heart rate variability, the system 90may increase the frequency resolution of a voice recognition system 84such that more types of audio features can be identified, albeit atperhaps a higher power consumption expense. In contrast, when the stresslevel is determined to be sufficiently low, the system 90 may decreasethe frequency resolution of a voice recognition system 84, such thatprocessing power may be saved.

As illustrated in FIG. 20, changing the appearance of a user interface(Block 708) may include increasing user interface brightness and/or fontsize of alphanumeric characters displayed on the user interface inresponse to detecting an increase in subject stress level (Block 718),and decreasing user interface brightness and/or font size ofalphanumeric characters displayed on the user interface in response todetecting an decrease in subject stress level (Block 720). For example,if the system 90 of FIG. 4 determines that the subject is experiencing acertain level of stress, such as the subject having an elevatedbreathing rate in context of low physical activity, the system 90 mayincrease the brightness of a screen and/or increase the font size oftext on a mobile device, such that it is easier for the subject tointerpret the screen, albeit at perhaps a higher power consumptionexpense. In contrast, when the stress level is determined to besufficiently low, the system 90 may decrease the screen brightnessand/or decrease the font size of text.

Example embodiments are described herein with reference to blockdiagrams and flowchart illustrations. It is understood that a block ofthe block diagrams and flowchart illustrations, and combinations ofblocks in the block diagrams and flowchart illustrations, can beimplemented by computer program instructions that are performed by oneor more computer circuits. These computer program instructions may beprovided to a processor circuit of a general purpose computer circuit,special purpose computer circuit, and/or other programmable dataprocessing circuit to produce a machine, such that the instructions,which execute via the processor of the computer and/or otherprogrammable data processing apparatus, transform and controltransistors, values stored in memory locations, and other hardwarecomponents within such circuitry to implement the functions/actsspecified in the block diagrams and flowchart block or blocks, andthereby create means (functionality) and/or structure for implementingthe functions/acts specified in the block diagrams and flowchart blocks.

These computer program instructions may also be stored in a tangiblecomputer-readable medium that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instructions whichimplement the functions/acts specified in the block diagrams andflowchart blocks.

A tangible, non-transitory computer-readable medium may include anelectronic, magnetic, optical, electromagnetic, or semiconductor datastorage system, apparatus, or device. More specific examples of thecomputer-readable medium would include the following: a portablecomputer diskette, a random access memory (RAM) circuit, a read-onlymemory (ROM) circuit, an erasable programmable read-only memory (EPROMor Flash memory) circuit, a portable compact disc read-only memory(CD-ROM), and a portable digital video disc read-only memory(DVD/BlueRay).

The computer program instructions may also be loaded onto a computerand/or other programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer and/or otherprogrammable apparatus to produce a computer-implemented process suchthat the instructions which execute on the computer or otherprogrammable apparatus provide steps for implementing the functions/actsspecified in the block diagrams and flowchart blocks. Accordingly,embodiments of the present invention may be embodied in hardware and/orin software (including firmware, resident software, micro-code, etc.)that runs on a processor such as a digital signal processor, which maycollectively be referred to as “circuitry,” “a module” or variantsthereof.

It should also be noted that in some alternate implementations, thefunctions/acts noted in the blocks may occur out of the order noted inthe flowcharts. For example, two blocks shown in succession may in factbe executed substantially concurrently or the blocks may sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved. Moreover, the functionality of a given block of the flowchartsand block diagrams may be separated into multiple blocks and/or thefunctionality of two or more blocks of the flowcharts and block diagramsmay be at least partially integrated. Finally, other blocks may beadded/inserted between the blocks that are illustrated. Moreover,although some of the diagrams include arrows on communication paths toshow a primary direction of communication, it is to be understood thatcommunication may occur in the opposite direction to the depictedarrows.

The foregoing is illustrative of the present invention and is not to beconstrued as limiting thereof. Although a few exemplary embodiments ofthis invention have been described, those skilled in the art willreadily appreciate that many modifications are possible in the exemplaryembodiments without materially departing from the teachings andadvantages of this invention. Accordingly, all such modifications areintended to be included within the scope of this invention as defined inthe claims. The invention is defined by the following claims, withequivalents of the claims to be included therein.

That which is claimed is:
 1. A monitoring device configured to beattached to a subject, the monitoring device comprising: aphotoplethysmography (PPG) sensor configured to measure a plurality ofphysiological parameters from the subject, wherein each physiologicalparameter is measured in a respective one of a plurality of timeintervals; at least one motion sensor configured to detect an activitystate of the subject; and at least one processor coupled to the PPGsensor and the at least one motion sensor, wherein the at least oneprocessor instructs the PPG sensor to measure a first one of theplurality of physiological parameters if the activity state is at orabove a threshold, and to measure a second one of the plurality ofphysiological parameters if the activity state is below the threshold.2. The monitoring device of claim 1, wherein the at least one processoris further configured to cause an optical emitter of the PPG sensor tohave a different polling rate in each of the respective time intervals.3. The monitoring device of claim 1, wherein the at least one processoris further configured to cause an optical detector of the PPG sensor tohave a different sampling rate in each of the respective time intervals.4. The monitoring device of claim 1, wherein the at least one processoris further configured to cause an optical detector of the PPG sensor toemit a different wavelength of light or a different set of wavelengthsof light during each of the respective time intervals.
 5. The monitoringdevice of claim 1, wherein the PPG sensor is configured to measuresubject heart rate in a first one of the time intervals, subject RRi ina second one of the time intervals, subject blood pressure in a thirdone of the time intervals, and subject breathing rate in a fourth one ofthe time intervals.
 6. The monitoring device of claim 1, wherein themonitoring device is configured to be positioned at or within an ear ofthe subject.
 7. The monitoring device of claim 1, wherein the monitoringdevice is configured to be secured to an appendage of the subject.
 8. Amethod of monitoring a subject via a monitoring device attached to thesubject, wherein the monitoring device comprises a photoplethysmography(PPG) sensor configured to measure a plurality of physiologicalparameters from the subject, at least one motion sensor, and at leastone processor, the method comprising: detecting an activity state of thesubject via the at least one motion sensor; and instructing the PPGsensor to measure a first one of the plurality of physiologicalparameters if the activity state is at or above a threshold, and tomeasure a second one of the plurality of physiological parameters if theactivity state is below the threshold.
 9. The method of claim 8, whereinthe monitoring device is configured to be positioned at or within an earof the subject.
 10. The method of claim 8, wherein the monitoring deviceis configured to be secured to an appendage of the subject.
 11. Amonitoring device configured to be attached to a subject, the monitoringdevice comprising: a photoplethysmography (PPG) sensor configured tomeasure subject heart rate, subject RRi, subject blood pressure, andsubject breathing rate; at least one motion sensor configured to detectan activity state of the subject; and at least one processor coupled tothe PPG sensor and the at least one motion sensor, wherein the at leastone processor is configured to instruct the PPG sensor to measure heartrate and/or breathing rate if the activity state of the subject is at orabove a threshold, and to measure RRi and/or blood pressure if theactivity state of the subject is below the threshold.
 12. The monitoringdevice of claim 11, wherein the PPG sensor is configured to measure thesubject heart rate in a first one of a plurality of time intervals, thesubject RRi in a second one of the plurality of time intervals, thesubject blood pressure in a third one of the plurality of timeintervals, and the subject breathing rate in a fourth one of theplurality of time intervals.
 13. The monitoring device of claim 12,wherein the at least one processor is configured to cause an opticalemitter of the PPG sensor to have a different polling rate in at leasttwo of the respective time intervals.
 14. The monitoring device of claim12, wherein the at least one processor is configured to cause an opticaldetector of the PPG sensor to have a different sampling rate in at leasttwo of the respective time intervals.
 15. The monitoring device of claim12, wherein the at least one processor is configured to cause an opticaldetector of the PPG sensor to emit a different wavelength of light or adifferent set of wavelengths of light during at least two of therespective time intervals.
 16. The monitoring device of claim 11,wherein the monitoring device is configured to be positioned at orwithin an ear of the subject.
 17. The monitoring device of claim 11,wherein the monitoring device is configured to be secured to anappendage of the subject.
 18. A method of monitoring a subject via amonitoring device attached to the subject, wherein the monitoring devicecomprises a photoplethysmography (PPG) sensor configured to measuresubject heart rate, subject RRi, subject blood pressure, and subjectbreathing rate, at least one motion sensor, and at least one processor,the method comprising: detecting an activity state of the subject viathe at least one motion sensor; and instructing the PPG sensor tomeasure heart rate and/or breathing rate if the activity state of thesubject is at or above a threshold, and to measure RRi and/or bloodpressure if the activity state of the subject is below the threshold.19. The method of claim 18, wherein the monitoring device is configuredto be positioned at or within an ear of the subject.
 20. The method ofclaim 18, wherein the monitoring device is configured to be secured toan appendage of the subject.